The article was published in a peer-reviewed journal.

Given the focus on inpatient settings, articles were included if they focused on mental health in the context of an inpatient setting, including planned and released inpatients, as well as multiple settings if inpatients were also considered. Studies with an exclusive focus on outpatient settings were not included. Studies including both outpatient and inpatient settings were included, while reports on these studies focused on the results with inpatients.

Given the focus on EMH tools, articles were included if they focused on EMH tools in the treatment of mental health. Digital procedures focusing solely on physical health or not designed to affect outcomes related to mental health (eg, online surveys on mental health with the purpose of collecting data) were not included.

Given the rapid technological development and improvement of EMH tools, older studies are expected to use outdated digital tools that may not represent current and future EMH technologies. More recent developments, innovations, and implementations in EMH include artificial intelligence (AI); virtual reality; chatbots; programs to detect emotion, voice, and cognition; various EMH apps; and general improvements in digital quality [35,36]. In addition, the COVID-19 pandemic further urged a transformation of EMH tools and services, leading to changes in both the quantity [37] and quality [38] of EMH tools. Hence, while earlier EMH literature focused on EMH tools as additives to treatment [39], contemporary literature focuses on a more holistic digitalization of mental health care [40]. Hence, earlier EMH literature may not adequately reflect the scope of contemporary EMH tools. As a cutoff date to exclude such earlier literature, articles were included only if they were published after January 1, 2015.

Due to the authors’ lingual constraints, only articles in English and German were considered.

Finally, articles were included if they were available. Articles that could not be found in full length, even after an extensive search, were excluded.

Only 2 articles focused on online inpatient preparation. One study examined an internet-based preparatory treatment consisting of informational modules to prepare patients in advance of their inpatient stay and to reduce uncertainty about the treatment [42]. Results found significant improvements in psychological, physical, and social problems, although there was no difference in the length of hospital stay. Providers showed a high acceptance and saw numerous advantages such as sharing of clear up-to-date information, ease of use, quick accessibility, and low cost. Another study investigated patients’ and clinicians’ expectations of an online inpatient rehabilitation preparatory platform [43]. Patients mentioned text-heavy information as a limitation of contemporary online information that may be improved via visualization, videos, and adaptive information display. Preparation platforms may also be improved by focusing on the efficacy and long-term benefits of treatments.

Interventions included Deprexis (an online self-help program [44-47]), REMOTION (an emotion regulation tool [48,49]), Moodgym (a CBT self-help tool [50]), SlowMo (a cognitive restructuring tool for paranoid beliefs [51]), Minddistrict (a transdiagnostic self-help tool [52]), a digital documentation or information tool [53], interactive modules including trainings and information [54-58], a digital self-guided assessment [59], a group training to improve social skills [60], and CBT online training [61].

In general, studies on EMH-related blended inpatient interventions reported good acceptance [45,48,50,52,55-57,61] and high satisfaction [62]. Six studies also found a significant improvement in symptoms [44-47,54,55], while 1 study found no significant improvement [48]. No studies reported worsening of symptoms. Adherence was deemed low to moderate, with great variation across studies. The full completion rate ranged from 7.6% [54] to 93% [60]. Similarly, use ranged from 17% [57] to 95% [47]. A desired but low use of EMH tools has been reported in a survey on inpatient practitioners [63] and in a qualitative interview of EMH tools [64].

The studies including Deprexis (all implemented in Germany) reported significant reductions of depressive symptoms in the intervention group. Deprexis consists of digital modules in addition to inpatient treatment, with training, information, and questions for patients to answer at different follow-up times. Acceptance was regarded as good. According to the authors, refusal rates were low (30%) when compared to other studies containing an online intervention, which reported refusal rates as high as 57% [8,39,44].

One study examined the use of a digital monitoring tool called Tele-Board MED [53], which was implemented in addition to inpatient treatment to promote patient-provider collaboration in medical encounters. It was found to improve patient engagement in the treatment process, communication, and collaboration. However, acceptance was not reported, and no control group was assessed for comparison.

Two studies implemented programs to use and understand one’s own emotions during inpatient treatment through a digital application [54,55]. Both these studies included inpatient and outpatient groups, which showed significant improvements in anxiety [54], depression, and emotional competency [55]. Although both studies showed improved mental health and high acceptance, adherence was reported as relatively low, with only 7.6% [54] or 13.4% [55] of participants completing all units of the treatment plan.

Interactive modules were used in various ways in 3 studies [56-58]. The studies by Schwarz et al [57] and Van Assche et al [58] focused on patients with depressive symptoms, and the study by Hammond et al [56] considered substance use. The modules contained information as well as interactive elements in the form of training [57,58]. Among these 3 studies, only the study by Hammond et al [56] used a treatment as usual (TAU) control group, while no control group was assessed in the other 2 studies [56]. Two studies stated seemingly high self-reported acceptance, with a patient usage rate of 54% [57] or 58% [56].

In another study, online CBT was offered in addition to TAU for patients with anxiety [61]. Only overall satisfaction and acceptability were measured, and mixed results were reported. Although 86% of patients participated, the completion rate was rather low at 55%. Some participants found the application useful, but others mentioned negative aspects, such as the triggering of negative thoughts through the intervention, which were reported during semistructured interviews at the end. Anxiety and depression scores did not differ between those who received online CBT and those in the TAU control group [61].

Levis et al [59] examined a mindfulness intervention based on the Whole Health approach. The intervention offered diagnostic prompts to identify behavioral patterns and therapeutic exercises to change patterns. There was no direct question of acceptance, but different questions regarding satisfaction with the program were assessed, and participants showed high satisfaction with the intervention, according to the authors [59].

Wälchli et al [48] investigated the efficacy of using the REMOTION tool as an addition to inpatient psychiatric care. Although usability and satisfaction were good, adherence was low, and no significant differences in symptom severity were found.

Four studies conducted qualitative interviews with patients and staff on the use of blended EMH interventions [49,51,52,65]. The importance of human interaction and therapist guidance emerged in 2 studies, in addition to concern regarding technology and previous experience [49,51]. Two studies mentioned the fit of the implementation setting as a potential barrier [49,52], and 1 study focused on staff concerns such as increased workload and insufficient time [52]. One study mentioned concerns regarding patient safety and changes necessary for the inpatient unit [65]. Nevertheless, the qualitative interviews reinforced the use of EMH as blended complements, especially when combined with non-EMH social support, which was reported by patients [49,51,52].

In summary, the majority of studies reported promising efficacy, high acceptance, and good satisfaction of blended EMH inpatient interventions. The efficacy of blended EMH treatment was also found in a previous systematic review and meta-analysis [20]. However, adherence to EMH treatment was low, with wide ranges of adherence reported by studies. Studies generally remarked that further research must be carried out to confirm the results and to identify further aspects that should be considered.

EMH aftercare is defined as online treatment starting after discharge from inpatient treatment.

Of the 90 articles, 13 were classified as EMH aftercare. The main goal of EMH aftercare was the outpatient maintenance or improvement of treatment gains achieved during inpatient treatment. EMH implementations included asynchronous mobile apps containing different modules [66-70], regular text messages with information regarding further treatment or information promoting mindfulness [71-73], chat forums with other former patients [74,75], online CBT [46,76-81], online self-management for anorexia nervosa [82-84], supportive-expressive therapy [85,86], ecological momentary assessment [87], and peer coach–based recovery [88]. Although EMH aftercare was mostly offered in relation to depressive symptoms, some treatment plans were focused on other diagnoses, including psychotic disorders and eating disorders. Control groups were used in all but 7 studies [74,81,83,84,86-88]. Some control groups received access to a selection of publicly accessible information regarding stress management and coping [68], mindfulness [71], depression [80], or health-promoting behaviors [85], or were waitlist control groups [73,77].

Overall, the results regarding depressive or affective symptoms were mixed. Five studies found significant improvements in depressive symptoms compared to the control group [46,55,68,73,77,80], while 1 study found none [67]. Significant symptom improvements were further observed in a transdiagnostic sample [77] and in work-related rehabilitation aftercare [85,86]. Meanwhile, 2 studies on eating disorders [77,82], 1 study on psychotic symptoms [72], and 3 studies on somatic comorbidities [70,75,78] found no significant improvements.

Acceptance was generally reported as high. Five studies reported good acceptance despite no direct measurement [55,67,68,71,77], and 8 further studies reported high acceptance with measures of acceptance, satisfaction, recommendation, helpfulness, or similar [69,72,75,77,79,81,83,86].

Reports of adherence were widely mixed, including assessments of low [73-78,82], moderate [68,70,71,85,86,88], and high [66,67,69,72,79,81] adherence. The rate of completion ranged from 1% [78] and 8% [74] to 95% [72] and 97% [67]. Similarly, the proportion of participants who used EMH tools at least once ranged from 36% [76] to 91% [85] or 100% [66].

Two studies conducted qualitative interviews on experiences with EMH tools (both involved ECHOMANTRA) [83,84]. Participants reported that despite general acceptance, increased personalization or tailoring may improve the experience. Social support, connections with other patients, and the involvement of carers were seen as great benefits. Self-monitoring reportedly increased participants’ self-awareness. The material was seen as useful and easy to access, yet the acceptability of remote support was mixed.

In summary, the results on the efficacy of EMH aftercare interventions were mixed to positive, complementing previous systematic reviews and meta-analyses on the positive effects of EMH aftercare [20,89]. Acceptance, satisfaction, and similar measures showed that EMH aftercare tools are generally well-received. However, aftercare studies reported wide variations in adherence and engagement, ranging from very low to very high. Thus, while EMH aftercare programs are promising and well-regarded tools for posttreatment inpatient stabilization, low and unpredictable adherence remains a limitation for reliable implementation.

Two studies focused on remote treatment procedures, with EMH interventions fully replacing indicated inpatient treatment [90-92]. Rauschenberg et al [90] described inpatient-equivalent treatment as an alternative that fulfills the requirements of psychiatric inpatient treatment conducted in a home environment. EMH tools, including ecological momentary assessments and digital feedback, further allow the implementation of adaptive digital interventions that adapt to the daily needs and momentary assessments of patients. Farrington et al [92] meanwhile conducted qualitative interviews and remote treatment as alternatives to inpatient treatment implemented when the health care system was disrupted during the COVID-19 pandemic: remote home care was found to be a satisfactory alternative to inpatient care, although the importance of social connections was emphasized.

In general, research on EMH-supported inpatient treatment alternatives is lacking, yet limited results are initially promising.

As previously mentioned, the acceptance and satisfaction of blended inpatient treatment or aftercare were generally good. Beyond these, acceptance was examined as the primary focus in several studies. These studies were conducted in a variety of settings, including inpatient [24,64,89,93-97] and inpatient-outpatient mixed [98] facilities. Both patients and professionals were assessed, and the results were reported in several studies. Results regarding patients were either obtained through specific acceptance questionnaires, including the UTAUT [89,93], a patient preference survey [98], USE [95], and semistructured interviews [96]. The acceptance of interventions from the perspective of health professionals was also evaluated, with questionnaires based on the UTAUT model [89,94,97]. The professional perspective was predominantly evaluated through the analysis of individual responses, which were obtained through conducting interviews by sending out a qualitative survey [24,95], through semistructured interviews [99], or with a direct questionnaire [51] by solely assessing user experience. Greenwood et al [51] demonstrated a beneficial outcome by assessing core themes related to the approaches and challenges of technology or improvements in paranoia and well-being. Another study [100] interviewed health care professionals regarding the use of inpatient telepsychiatry: telepsychiatry generally improved the care process by addressing the needs of patients and carers. Dewa et al [101] found passive monitoring systems in forensic psychiatric hospitals to be generally acceptable, although acceptance was decreased when knowledge of the technology was low. Hennemann et al [94] offered a review on current studies highlighting acceptance among health care professionals. In general, 88% of participants among all studies reported low to moderate acceptance, with only 21% of all participants indicating a sufficient eHealth training. They did find, however, that 75% would reconsider using an eHealth intervention after appropriate education.

The majority of studies found moderate to high acceptance either through direct measurement with validated tests or through an analysis of qualitative answers [45,48,50,52,55-57,61,69,72,75,77,79,81,83,86]. However, 3 studies [89,93,97] reported low or mixed acceptance, such as low to moderate acceptance for general acceptance, as well as moderate acceptance among patients (57.1%) but low acceptance among professionals (29.6%) [89]. Sander et al [97] demonstrated a low acceptance rate, as measured by the Attitude toward Telemedicine in Psychiatry and Psychotherapy scale, with mixed responses for specific questions such as agreement to online therapy as a good addition (77%) or recommendation of online therapy to patients (36%). Some studies reported that patients hold a predominantly positive attitude toward online therapy [64,95,98], although 1 study also highlighted a high dropout rate of 43% [95]. Differences in acceptance rates between studies may be due to different methods of assessing acceptance and differences in knowledge or technical prerequisites.

In summary, the acceptance of EMH tools is generally high and tends to be higher for patients than for health care staff. Acceptance may be further improved by (1) increasing transparency and knowledge regarding EMH tools, including staff training [98,101]; (2) improving aspects of EMH content, such as visualization [43] and personalized tailoring [83]; (3) facilitating the role of social support, social connections, and caretaker guidance [49,51,83,92]; and (4) considering staff’s workload and time constraints [52,62]. However, high dropout rates may bias the results on high acceptance as low acceptance by patients may be a reason to stop treatment.

As previously mentioned, adherence to EMH-supported interventions varied greatly across studies and tended to be low. This is despite the promising efficacy and good acceptance of EMH tools. Two studies reported good usability but low actual usage [63,64], despite the majority of patients in inpatient care having access to mobile devices [100]. Hence, adherence appears to be a major limitation in the realization of EMH-supported interventions.

Two studies implemented interventions to improve digital acceptance and literacy [55,102]. Kreis et al [55] implemented an acceptance intervention for the online self-help tool KEN-Online, which increased acceptance and initial use by 20% compared to the passive control group, yet adherence as measured by the rate of completers remained low at 13.4%. Hence, the acceptance intervention mainly showed initial effects. Camacho et al [102] conducted DOORS digital literacy training. Although digital skills were improved by the intervention, there were no significant effects on symptom reduction, and adherence was not reported.

Given the limited number of studies and modest findings, an empirical investigation on interventions to increase EMH tool adherence remains an open issue.

Eleven articles included in this scoping review are reviews or meta-analyses [20,89,103-111]. Among these, 1 systematic review by Henneman et al [89] focused on the efficacy of EMH inpatient aftercare based on 16 RCTs, and 1 meta-analysis by Diel et al [20] focused on the efficacy of blended and aftercare EMH inpatient treatment based on 26 RCTs. The results support the efficacy of EMH inpatient treatment, concerning both blended treatment and aftercare, and across a variety of mental disorders. However, both reviews noted the limitation of the small number of studies, especially for subgroup analyses. Hennemann et al [89] further noted partial inconsistencies in results for EMH aftercare treatments.

Three reviews focused on EMH-supported interventions for both inpatient and outpatient treatment [103,104,110]. Erbe et al [103] found that blended treatment may improve time efficiency and the dropout rate, yet they remarked about a lack of appropriate research. Dülsen et al [104] noted the initial promise of EMH tools in inpatient treatment but called for further research on potential barriers and the development of proper protocols. Ehrt-Schäfer et al [110] also found promise for blended psychotherapy yet cautioned against generalizations.

The remaining 6 reviews focused on the treatment of specific disorders or symptoms, including but not necessarily limited to inpatient and EMH interventions [105-109,111]. Sweetman et al [105] investigated CBT treatment for insomnia on sedative-hypnotic use and found promising yet limited results from digital CBT. Spanakis et al [106] investigated behavioral smoking cessation treatment but found limited results for digital treatments. Liu et al [107] found that online mindfulness-based interventions can elevate symptoms in patients with physical health symptoms. Castle et al [108] found an initial promise of digital interventions for obsessive-compulsive disorder. Loh et al [109] investigated mobile health interventions in the treatment of psychotic disorders, found a wide variety of applications and settings, and urged holistic evaluations of EMH applications. Finally, Shin et al [111] investigated the trends of EMH applications for suicide prevention. The interest in digital suicide prevention is increasing and includes postdischarge follow-up, screening or assessment, and safety planning, but research is lacking, especially on long-term outcomes.

Nine of the included articles were study protocols [112-120], and 6 studies were essays or commentaries [90,121-125]. Baumeister et al [121] provided a description of blended psychotherapies, dividing them into sequential blended treatments, including stepping up (digital interventions preceding in-person treatment, for example, as a preparation or to bridge waiting times) and stepping down (digital interventions following in-person treatment, for example, as aftercare), and integrated treatments, including complementing digital sessions, resource-driven replacement of in-person sessions, and improvement of in-person sessions using digital tools. Rauschenberg et al [90] presented inpatient-equivalent treatment using digital support. Hirjak et al [122] emphasized the ethical and scientific challenges of implementing EMH in mental health treatment. Feinstein [123] presented and suggested the use of EMH tools in crisis intervention psychotherapy during the COVID-19 pandemic. Inchausti et al [124] commented on the challenges caused by the COVID-19 pandemic and the potential benefits of telepsychiatry regarding those challenges, including underestimation of damage, resource deficits, poor planning and coordination, and risks of early crisis responses. Finally, Westheimer et al [125] presented a model to implement digital tools in inpatient mental health care, the Technology Implementation for Mental Health End Users (TIME) framework, focusing on the interplay and communication between “high-tech” digital tool development and “high-touch” in-person treatment.

Five articles focused on the use of EMH during the COVID-19 pandemic [91,123,124,126,127]. One study examined the experiences of patients during the COVID-19 pandemic [126]. One article was a commentary on telepsychotherapy during the pandemic [124]. Another article provided a description of crisis intervention during the pandemic [123], and another article mentioned the effect of online psychoeducation on patients during the pandemic [127].

Favorable views have been reported by Schlegl et al [126], Inchausti et al [124], and Shaygan et al [127], with the latter reporting successful implementation with the mitigation of stress and promotion of resilience. These articles did not provide a conclusive overview since they were very specific in their research questions and therefore could not be compared [124,126,127].

Four articles were classified as “others” [43,62,63,128]. The articles presented an overview of the perspectives of rehabilitants regarding digital information before inpatient psychosomatic care [43], a description of eHealth use in inpatient mental health units regarding barriers or benefits [63], a description of digital symptom monitoring offered during inpatient treatment [62], and a survey on EMH inpatient use [128]. The articles reported EMH tools as potentially helpful according to participants, and the article on the information program before inpatient care reported uncertainty regarding effectiveness but outlined the importance of familiarizing patients with the effectiveness and sustainability of the inpatient program [43]. Chat- and phone-based EMH tools were most commonly used according to a survey [102]. One study showed that patients preferred the digital version of symptom monitoring to the analog version [62]. The main barriers reported in the survey filled out by staff in inpatient units were unclear roles, dwindling implementation support, a high workload, and a high number of administrative tasks [63].

A summary of the use of EMH tools and their potentials and concerns based on the scoping review is shown in Figure 2.

The inpatient journey can be divided into 3 treatment steps (preparation, inpatient treatment, and aftercare) and 3 transitory steps (recruitment/screening, adherence/digital training, and return to work/outpatient transition). Along all 6 steps, the implementation of EMH tools has been investigated in research. Across treatment steps (preparation, blended/remote treatment, and aftercare), both efficacy and acceptance have been shown [20]. However, low adherence has remained a consistent issue for the implementation of EMH tools [63,64]. Although EMH-assisted inpatient preparation shows potential [42], research is currently lacking. Digitally assisted recruitment and screening can allow a wider outreach of patients and efficient provision of information [9,11], and interventions focusing on the improvement of digital treatment (eg, adherence and digital literacy training) may counteract the common disadvantages of EMH tools, most notably low adherence. However, such interventions also show limited research, which, thus far, has not shown promising results [55]. Although posttreatment return-to-work treatments show promise [68], other types of posttreatment transition-based interventions have shown limited effectiveness [60,82].

In summary, while research generally supports EMH-assisted treatment in terms of efficacy and acceptance, low adherence remains a common issue. While transitory and preparatory interventions with EMH support are promising tools to enhance the inpatient journey, there is currently limited research available for their critical evaluation.

In 8 studies investigating adherence, dropout rates were higher in interventions containing some sort of online element than in face-to-face interventions due to low adherence. This could have impacted the measured acceptance or effectiveness as low acceptance of effectiveness cases may have dropped out [72,94]. Additionally, willingness to participate was generally low, with various authors describing a low percentage of patients interested in participating. As a result, sample sizes were sometimes not achieved, and unwilling patients were assessed as a control group. This could have affected the treatment effects. Although adherence-improving interventions have been investigated, their results remain modest [55].

Given the wide range of included studies, several concerns on methodological quality emerged. Future research should increase sample sizes as many presented samples were small, undermining statistical power. Replications featuring larger sample sizes are necessary to ensure representativeness and generalizability.

The included studies additionally predominantly featured specific patient groups, sometimes without a control group. For future research, programs should be tested in comparison with a control group and relevant patient groups to investigate significant effects and assess efficacy.

Acceptance measures were heterogeneous, and many studies did not directly measure acceptance in any way. Future research should aim to use standardized measures of acceptance to allow proper assessment and comparisons between studies.

Concerns about data security and privacy are common in the context of EMH [11], which is especially relevant given the vulnerability of psychiatric patients. Patients may experience an invasion of privacy caused by passive monitoring systems and an imbalance in the power dynamic [101] or by sensitive data being shared [124]. Clinical staff also noted data security risks caused by digital data storage, for example, through hacking attempts [99]. In 1 survey, privacy concerns were reported by 35.9% of practitioners [24]. Many data security concerns on EMH tools in general can be applied to inpatient settings, such as risks caused by digital security breaches associated with hackers or corporations [132,133]. Inpatient settings allow new data security risks to emerge, for example, through breaches caused by other inpatients [124]. However, the presented literature has not sufficiently presented solutions to potential security concerns. Future research may focus on security concerns in the context of EMH inpatient care.

The concern of EMH tools substituting human interaction has been raised in the past [134]. In inpatient settings, qualitative interviews showed that the importance of human interactions has been raised by both patients and clinical practitioners [24,49,51,83,92], and EMH tools in inpatient care showed increased acceptance when framed as enhancements rather than replacements of face-to-face treatment [99]. Meanwhile, EMH tools showed the greatest effectiveness when used and supported by humans [135]. In order to minimize risks and fears about EMH tools replacing face-to-face human interaction, practitioners may focus on implementing EMH tools alongside human interaction if possible and enlighten patients on how EMH tools are supposed to enhance, rather than replace, in-person treatment.

Practical concerns on the implementation of EMH tools are prevalent in inpatient settings. Those include concerns on the fit of EMH tools in inpatient settings [49,52], insufficient digital infrastructure [63], staff workload issues [52,62], and lack of knowledge or expertise among staff or patients [24,49,63,101]. The variety of implementation limitations suggests the need for proper preparation of the inpatient setting, infrastructure, treatment, and clinical staff in order to efficiently implement EMH tools into inpatient treatment routines.

There is a lack of research on both EMH-supported inpatient preparation and interventions aimed at improving EMH-supported treatment. This is surprising given that both aspects show noteworthy potential: EMH-supported inpatient preparation may be used to improve inpatient treatment efficacy while also providing an opportunity to support patients during the vulnerable waiting time. Meanwhile, interventions aimed at improving EMH-supported treatment (eg, digital literacy or digital adherence training) may counter common limitations and concerns of EMH treatment, namely lack of knowledge or experience and low adherence. An EMH-based preparation may even combine inpatient preparation, waiting time bridging, and digital training to support and prepare patients for an EMH-supported inpatient treatment. Hence, such preparatory interventions may be investigated in future research.

The role of demographic and clinical diversity in the acceptance and efficacy of EMH-based treatment has not been sufficiently explored. Subgroup analyses based on patient diagnoses showed EMH efficacy for various disorders [20]; however, the number of studies was too small to conduct proper subgroup analyses. One study did not find demographic moderators for symptom outcomes [47]. On the other hand, EMH tools may be tailored to specific demographics to increase efficacy or acceptance [64]. Understanding the interactions between patient demographics and EMH tool acceptance and efficacy may help by providing specific recommendations and allowing tailoring of EMH tools to patients’ needs according to their demographics.

Remote alternatives to inpatient treatment may also be further investigated. Inpatient-equivalent treatment (German: stationsäquivalente Behandlung [StäB]) has been established in Germany recently and can be used in medically appropriate cases, in which the treatment can be allocated. It was established in 2017 and sets the same requirements regarding patients as for inpatient treatment in a ward. Patients are offered the possibility of one-to-one meetings with a therapist while in treatment as well as group therapy, and accompaniment and training in daily life. As a requirement, all people living in the household must agree to the treatment, although an opportunity to talk with the patient privately must be given. Daily contact must be possible between patients and treatment providers, and documentation must be to the same standard as inpatient treatment. Not all clinics offer the inpatient equivalent for outpatient care so far, but it is being implemented more frequently [136]. Considering the growing evidence of EMH, this concept might be extended by adding EMH to the treatment plan.

Although a prior meta-analysis showed long-term stability [20], the majority of research on EMH tools did not investigate long-term sustained improvements via follow-ups. Future research may focus on the long-term benefits of EMH-based inpatient interventions.